De novo Biosynthesis of Caffeic Acid and Chlorogenic Acid in Escherichia coli via Enzyme Engineering and Pathway Engineering

大肠杆菌 咖啡酸 代谢工程 绿原酸 生物合成 生物化学 合成生物学 蛋白质工程 化学 定向进化 生物 计算生物学 食品科学 基因 突变体 抗氧化剂
作者
Zhenyu Zhang,Pengfu Liu,Bin Zhang,Jian Shen,Jiequn Wu,Shusheng Huang,Xiaohe Chu
出处
期刊:ACS Synthetic Biology [American Chemical Society]
卷期号:14 (5): 1581-1593 被引量:5
标识
DOI:10.1021/acssynbio.4c00850
摘要

Caffeic acid (CA) and chlorogenic acid (CGA) have diverse health benefits, including hemostatic, antioxidant, and antiinflammatory, highlighting their potential for medical applications. However, the absence of high-performance production strains increases production costs, limiting their wider application. In this study, we engineered Escherichia coli for the de novo production of CA and CGA. To improve production, a highly efficient mutant tyrosine ammonia-lyase from Rhodotorula taiwanensis (RtTAL T415M/Y458F ) was identified using genome mining and protein engineering. By engineering the tyrosine biosynthetic pathway through the deletion of pheA and tyrR, along with the overexpression of aroG fbr and tyrA fbr, we developed an engineered E. coli strain, CA11, which produced 6.36 g/L of CA with a yield of 0.06 g/g glucose and a productivity of 0.18 g/L/h. This represents the highest titer reported for microbial synthesis of CA using glucose as the sole carbon source in E. coli . Based on strain CA11, we further developed strain CGA13, with optimized replicons, promoters, and ribosome-binding sites, which produced 1.53 g/L of CGA in fed-batch fermentation, highlighting its potential for industrial-scale production.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
思源应助科研通管家采纳,获得10
刚刚
刚刚
Lucas应助科研通管家采纳,获得10
刚刚
NexusExplorer应助科研通管家采纳,获得10
刚刚
paradox应助科研通管家采纳,获得10
刚刚
orixero应助科研通管家采纳,获得10
刚刚
1秒前
blackcat完成签到 ,获得积分10
1秒前
释然zc发布了新的文献求助10
1秒前
pppxw应助科研通管家采纳,获得10
1秒前
txx发布了新的文献求助10
1秒前
aaaa应助科研通管家采纳,获得10
1秒前
orixero应助科研通管家采纳,获得10
1秒前
CodeCraft应助科研通管家采纳,获得10
1秒前
1秒前
Jasper应助科研通管家采纳,获得10
2秒前
搜集达人应助科研通管家采纳,获得10
2秒前
赘婿应助科研通管家采纳,获得10
2秒前
CipherSage应助喵先生采纳,获得10
2秒前
科研通AI6.3应助好运连连采纳,获得10
2秒前
隐形曼青应助科研通管家采纳,获得10
2秒前
可爱的函函应助savior采纳,获得10
2秒前
段非非发布了新的文献求助10
2秒前
Dormantparner发布了新的文献求助10
3秒前
3秒前
3秒前
小二郎应助lmn采纳,获得10
4秒前
4秒前
4秒前
kinksaber完成签到,获得积分10
4秒前
ansteel发布了新的文献求助20
5秒前
5秒前
5秒前
6秒前
丘比特应助vivi采纳,获得10
6秒前
6秒前
传统的孤丝完成签到 ,获得积分10
6秒前
WQ完成签到,获得积分10
6秒前
7秒前
7秒前
高分求助中
APA handbook of comparative psychology: Basic concepts, methods, neural substrate, and behavior 1000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
Römisch-Germanische Forschungen 500
Electric machines: theory, operating applications, and controls 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
When Is Two-Stage Sample Robust Optimization Asymptotically Optimal? 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7600541
求助须知:如何正确求助?哪些是违规求助? 9176876
关于积分的说明 19649868
捐赠科研通 7176412
什么是DOI,文献DOI怎么找? 3268723
关于科研通互助平台的介绍 2433062
邀请新用户注册赠送积分活动 2262308